News and Views on Social Marketing and Social Change

The 10 Best mHealth Papers of 2012

The mobile health (mHealth) space, especially as it relates
to health behavior change and chronic and infectious disease management, has
been a long running theme of mine for increasing reach, effectiveness,
efficiency and equity of interventions. (See Integrating cellphones and mobile technologies into public
health practice -pdf). The allure of mHealth, often promoted via stories, case studies and visions
of the mobile future, has raced ahead of most objective analyses. For the best mHealth papers of 2012, I selected ones that
address many important - but skimmed over - issues. The first paper examines how to assess health
systems, their readiness and capacity to scale up mHealth interventions.
This paper focuses on South Africa, but the framework and conclusions could fit
most developed and LMIC contexts. The article by Whittaker and colleagues
reflects on their experiences and discusses the important steps for developing quality mHealth
apps and evaluating their effectiveness. It is a paper that most app developers and mHealth designers
should put at the top of their reading list for 2013.

The next four articles are systematic reviews and
meta-analyses of mHealth interventions for, respectively, behavior change
programs in developing countries, increasing levels of physical activity, the
management of diabetes, and self-management of chronic illnesses. Each of these
areas generates a lot of excitement and buzz at mobile health conferences, but
as every one of these authors note, the evidence-base is both structurally weak
(poor research designs and data reporting) and inconsistent with respect to
outcomes.

The two papers that follow describe intervention trials. The
first utilizes an RCT to demonstrate the value of integrating mobile
technologies into standard care approaches to weight loss management. The second
study, a diabetes management program for low-income urban women, is significant
not so much for its findings but for its penetrating review of its
failures – the nearly 50% drop-out rate. All program designers should give this
one a careful read for the lessons it offers.

Finally, the last two articles look at the current and
future state of mHealth. Whittaker reports her findings from interviews with
key US mHealth stakeholders and Dolan wraps up the first year in which
FDA regulatory approval popped up on many developers’ radar; he notes that at
least 75 mHealth apps were approved by the agency.

“Several informants raised the concern that many mHealth
applications available in practice may not be effective, engaging, usable, or
meeting the needs of users. Few applications have been evaluated, and those
that have often involve complex interventions where the components or mechanisms
have not been examined. Many felt that not a lot is known as yet about what
aspects of mHealth work, for whom, and why. Few published health interventions
delivered via mobile technologies discuss a theoretical basis or evaluate
theoretical components hypothesized to be important in the intervention. It was
stated that there is much hype and lots of players all “doing their own thing.”
Some informants felt that some mHealth developers may have a bias toward
developing programs for people like themselves using the technologies they
like, rather than starting with the problem and working with end users to
develop the most useful and usable solution. Some pointed to statistics in the
media showing that many smartphone applications are downloaded but not used.
More recently, reviews have found poor quality in terms of accuracy, usability,
consistency with national practice guidelines, and effective practices.”

I suspect that if you read and apply the insights and
lessons from this top ten list, you might make significant contributions to the
solutions for these and other issues that perplex the field.

Applies a framework of
government stewardship and the organizational, technological and financial
systems of a health care system to assess the opportunities and challenges to
effectively implement mHealth interventions at scale. Stewardship includes strategic leadership and
creating a learning environment; organizational issues include having a culture
for use of health information for management, and a capacity for
implementation; technological components include usability, interoperability
and privacy and security safeguards; and financial system variables are
demonstrating the cost-effectiveness of mHealth approaches and having in place
sustainable funding sources.

Using examples of the
development of a video messaging smoking cessation intervention and a mobile
phone multimedia messaging depression prevention intervention, the authors describe
a series of steps for developing mHealth interventions: conceptualization,
formative research to inform the development of the intervention, pretesting
content, pilot study, pragmatic randomized controlled trial, and further
qualitative research to inform improvement or implementation. Several themes
underlie the entire process, including the integrity of the underlying behavior
change theory, allowing for improvements on the basis of participant feedback,
and a focus on implementation from the start. The strengths of this process are
the involvement of the target audience in the development stages and the use of
rigorous research methods to determine effectiveness.

The authors reviewed 44
articles; 16 (36%) reported evaluation data from mHealth interventions, mostly in
Africa and Asia. HIV/AIDS and family planning/pregnancy were the health topics
most frequently addressed by interventions. Studies did not consistently demonstrate
significant effects of exposure to mHealth interventions on the intended
audience. The majority of publications (n = 12) described interventions that
used two-way communication in their message delivery design. Although most publications
described interventions that conducted formative research about the intended
audience (n = 10), less than half (n = 6) described targeting or tailoring the
content.

The aims of this review were to: (1) examine the efficacy of mobile
devices in the physical activity setting, (2) explore and discuss
implementation of device features across studies, and (3) make recommendations
for future intervention development. After searching electronic databases, four research studies were considered to be of "good" quality and seven of
"fair" quality, involving a total of 1,351 participants. Their
meta-analysis of outcomes, duration of moderate to vigorous physical activity
and/or pedometer steps, provide some preliminary support for mobile technology
(SMS) interventions to increase physical activity behavior. They also note that
that much can be added to current theoretical models of behavior change so that
they are better suited to design mobile interventions and interpret results.

The investigators used database searches to identify studies
that investigated the clinical effectiveness of mobile-based applications that
allowed patients to record and send their blood glucose readings to a central
server; 24 papers were reviewed. Results for patients with type 1 and type 2
diabetes were examined separately. Study variability and poor reporting made
comparison difficult, and most studies had important methodological weaknesses.
Evidence for the effectiveness of mHealth
interventions for diabetes was inconsistent for both types of diabetes and
remains weak.

The authors conducted a review of experimental studies that assessed the
effects of mobile phone messaging applications on health outcomes and patients'
capacity to self-manage their condition. Four RCTs with a total of 182
participants were the focus of their analysis. They concluded that because of the small number
of trials included, and the low overall number of participants, the quality of
the evidence for positive impacts of SMS on health outcomes or self-management
capabilities can at best be considered moderate. Furthermore, the usefulness
and potential negative consequences of mobile phone messaging over extended
periods of use for self-managing long-term conditions are not yet known.

Notable for being an RCT
of a mHealth intervention, the current study demonstrates the feasibility of
using mobile connective technology to interface with a hospital based, standard-of-care
weight loss treatment. Adding technology and coaching to the standard-of-care
group obesity treatment significantly enhanced weight loss outcomes at 3, 6, 9,
and 12 months. More than 36% of participants using the mobile technology system
and coaching, compared with 0% in the standard-of-care condition, lost at least
5% of their initial body weight at 3 months and this effect was significant,
though less pronounced at 12 months (29.6% vs 14.8%).

An unflinching look at
the many lessons learned from a pilot study of a cell-phone assisted diabetes
self-management program carried out in an urban community clinic. There were
high no-show rates for the baseline visit (49%) and the drop-out rate for
participants was 50%. Six measures of diabetes standard-of-care improved; hospitalizations
and emergency department visits were reduced during the study period in
comparison with baseline.

The author conducted semi-structured interviews with 27 key
informants from across the health sector and mHealth sector in the US to
determine the important issues facing the implementation of mHealth. The most
common issues included privacy and data security, the regulation of mHealth tools and programs as medical
devices, the fragmentation and large number of wireless providers that makes
comprehensive implementation difficult, the costs of mHealth services to the
public, the proliferation of proprietary systems and multiple platforms, funding,
a lack of good examples of the efficacy and cost-effectiveness of mHealth in
practice, and the need for more high quality research.

The
emergence of FDA regulatory guidance this past year has led more
mHealth developers to submit their apps for review and approval. At least 75 510(k) clearances included a
mention or description of a mobile software component. Most FDA cleared apps
are focused on chronic condition management — often taking the form of a
digital logbook that receives data from a companion medical device. This group
includes diabetes, asthma, and blood pressure management apps. The next largest
contingent of FDA-cleared apps are related to electrocardiographs (ECGs), and
typically take the form of a remote, mobile viewer for ECG data. Vital sign
monitoring apps, imaging apps and medication adherence apps round out the group
with a few apps that don’t fit any of those categories. These findings are
compiled in the MobiHealthNews Research report: 75
FDA Regulated Mobile Medical Apps.